KLIP: localized distribution shift detection via KL-divergence with diffusion priors in Inverse Problems 事件

KLIP: localized distribution shift detection via KL-divergence with diffusion priors in Inverse Problems arXiv:2605.31596v1 Announce Type: new Abstract: Diffusion models have shown promising performance as data-driven priors for computational imaging, as well as some capacity to detect out-of-distribution (OOD) images. However, existing approaches to OOD detection often require some knowledge of the shifted distribution, fail to detect subtle or localized distribution shifts, and operate on ful